Digital subscriber lines (DSLs) offer carriers the possibility of exploiting the existing loop plant to deliver high-speed data and voice services. Today several types of Digital Subscriber Line (DSL) technologies are rapidly becoming standards for delivering access on copper access network cables to the end user. Examples of DSL technologies (sometimes called xDSL) include High Data Rate Digital Subscriber Line (HDSL), Asymmetric Digital Subscriber Line (ADSL), and Very-high-bit-rate Digital Subscriber Line (VDSL).
The DSL, which connects the customer premises (CP) to the central office (CO), has several impairments that are not present for the plain old telephony service (POTS) because xDSL exploits a much wider frequency band. As a consequence, the existing POTS testing equipment is not capable of accurately qualifying a subscriber loop for xDSL transmission. There are impairments causing attenuation, such as bridged taps, mixed wire gauge, and bad splices. In order to qualify a subscriber loop for xDSL transmission it is desired to fully characterize the subscriber loop, i.e., to identify its loop makeup. The loop (=line) make up implies in this description parameters such as the total length of the loop, number of sections, length and gauge (i.e. the diameter) of each section, splice location, and number of bridged taps and their position and length. Loop make-up identification allows telephone companies to update and correct their loop plant records. Therefore, accurate loop make-up identification can further be used to update records in loop databases, and such records can in turn be accessed to support engineering, provisioning and maintenance operations.
In this way, the development of automatic loop makeup techniques is very important for cost reduction during the service deployment stage and even afterwards, during preventive monitoring tests against eminent service failures. Nowadays, there are several works that address this issue, but the majority is focused on single-ended techniques referred to as Single ended Line Test (SELT). The SELT may be based on Time Domain Reflectometry (TDR). TDR implies an analysis of a loop (wire, cable, or fiber optic) by sending a pulsed signal into the loop, and then examining the reflection of that pulse. By examining the polarity, amplitude, frequencies and other electrical signatures of all reflections, tampering or bugs may be precisely located. Frequency-domain reflectometry (FDR) is another technique that SELT may be based on. In FDR, the loop is sounded with a swept sinusoid to identify frequencies that either resonate or are “dead.” For example, peaks in the measured receive signal correspond to frequencies that create standing waves. Standing wave frequencies provide information about the length of the cable.
Moreover, SELT may also be based on a parameter referred to as One-Port Scattering Parameter, denoted S11 or echo response: This method is similar to the FDR, but instead of looking for individual frequencies, a complete echo response measurement is utilized. From the echo response, the input impedance or S11 of the loop can be determined, from which the loop topology can be determined.
With the advent of G.992.3 and G.992.5 standards for ADSL 2 and ADSL 2+, modems with the function loop-diagnostic became possible. These modems located at the user side, jointly with the IPDSLAM (Internet Protocol Digital Subscriber Line Access multiplexer) located at the CO-side, enable measurement of the attenuation per tone, referred to as the transfer function, directly. As it is possible to have two port measurements, it is possible to determine the ratio between the signal at input and output of the line and thus a measurement of the transfer function can be obtained. This new functionality brings forth the perspective of new, reliable and precise techniques for loop makeup identification and supervising. Such two-terminal measurements are referred to as DELT (Double Ended Line Test), in contrast to the SELT.
The most common qualification method concentrates on mining on the existing data in loop databases, checking its accuracy, and then bulk-provisioning loops that are candidates for DSL-based service. Sometimes a combination of loop records and engineering information about feeder route topology is used to obtain an estimate of loop length. This technique presents quite imprecise estimative. Often such data are not reliable or non-existing. Furthermore, manual Loop Qualification (LQ) with human intervention is costly and open up for human errors.
A great number of articles about loop qualification (LQ) methods are based on TDR data obtained from SELT measurements. Previous attempts to use TDR techniques, sometimes coupled to artificial neural network algorithms, have failed due to the difficulty of the post-processing of the TDR trace needed to extract all loop features. Moreover, conventional metallic TDRs are not capable of detecting all reflections. In fact, conventional metallic TDRs cannot detect gauge changes and, moreover, have a serious range limitation that prevents them from detecting reliably echoes further than several kilometers (km) from the Central Office (CO). Besides, it is necessary with additional processing of the TDR data because accurate TDR measurements alone are not sufficient without an algorithm able to extract information from the TDR trace (i.e. TDR plot or curve). That implies that the additional time for this processing is required and the processing of the TDR data is not trivial and could be subjective, making automation of this technique very difficult. In particular, a major problem arises in a TDR approach since observations available at the receiver consist of an unknown number of echoes, some overlapping, some spurious, that exhibit unknown amplitude, unknown time of arrival and unknown shape. Thus, the conventional TDR technique can demand some modifications of the measurements setup and more complicated pre-processing as can be seen in K. J. Kerpez, S. Galli, “Single-Ended Loop Make-up Identification—Part I: Improved Algorithms and Performance Results,” IEEE Transactions on Instrumentation and Measurement, vol. 55, no. 2, April 2006.
Another type of single-ended technique for loop-qualification is proposed in T. Bostoen, P. Boets, M. Zekri, L. Van Biesen, T. Pollen and D. Rabijas, “Estimation of the Transfer Function of a Subscriber Loop by means of a One-Port Scattering Parameter Measurements at the Central Office.” IEEE J. Select. Areas Commun., pp. 936-948, Vol. 20, No 5, June 2002. According to this reference, it is proposed the use of the one-port scattering parameter S11 to achieve channel transfer function estimation when a priori information of the loop topology is available. Although this allows good results on short/medium length loops, the assumption that some or all the loop topology is known prior to testing may limit the practical applicability of this technique. In addition, the technique may present no feasible results, i.e., achieve non-physically loops.
From the G.992.3 and G.992.5 standards for ADSL 2 and ADSL 2+, the loop diagnostic functionality for modems was standardized, enabling double ended measurements (DELT). Thus with DELT, the direct loop transfer function estimation, i.e. the estimation of the attenuation per tone, can be measured without the need of auxiliary techniques. Such functionality is still under test and only a few papers are focused on transfer function measurements applied on loop makeup identification. In J. L. Fang, C. Zeng and J. Cioffi, “Bridged Tap Location Estimation,” Electrical Engineering Department, Stanford University, 2003, it is proposed a Bridged-tap location approach from transfer function measurements. But, this method addresses just simple loops with a single bridge-tap.
As described above, it is desired for telecommunication operators to identify the complete loop makeup e.g. in order to predict possible bit rates and other performance parameters in the network. However, the SELT and the DELT methods referenced above fail to accurately identify the complete loop make up.